Exploiting multiple languages and resources jointly for high-quality Word Sense Disambiguation and Entity Linking

Definitional knowledge has proved to be essential in various Natural Language Processing tasks and applications, especially when information at the level of word senses is exploited. However, the few sense-annotated corpora of textual definitions available to date are of limited size: this is mainly due to the expensive and time-consuming process of annotating a wide variety of word senses and entity mentions at a reasonably high scale. In this paper we present SENSEDEFS, a large-scale high-quality corpus of disambiguated definitions (or glosses) in multiple languages, comprising sense annotations of both concepts and named entities from a wide-coverage unified sense inventory. Our approach for the construction and disambiguation of this corpus builds upon the structure of a large multilingual semantic network and a state-of-the-art disambiguation system: first, we gather The work of Jose Camacho-Collados, Claudio Delli Bovi and Alessandro Raganato was mainly done at Sapienza University of Rome. http://lcl.uniroma1.it/sensedefs. & Jose Camacho-Collados camachocolladosj@cardiff.ac.uk Claudio Delli Bovi boviclau@amazon.com Alessandro Raganato alessandro.raganato@helsinki.fi Roberto Navigli navigli@di.uniroma1.it 1 Cardiff University, Cardiff, UK 2 Amazon.com, Inc., Turin, Italy 3 University of Helsinki, Helsinki, Finland 4 Sapienza University of Rome, Rome, Italy 123 Lang Resources & Evaluation (2019) 53:251–278 https://doi.org/10.1007/s10579-018-9421-3